fix chat-style prompt templates (#1970)

Also use a new version of Mistral OpenOrca.

Signed-off-by: Jared Van Bortel <jared@nomic.ai>

gpt4all-bindings/python/gpt4all/_pyllmodel.py

@@ -89,10 +89,12 @@ RecalculateCallback = ctypes.CFUNCTYPE(ctypes.c_bool, ctypes.c_bool)
 llmodel.llmodel_prompt.argtypes = [
     ctypes.c_void_p,
     ctypes.c_char_p,
+    ctypes.c_char_p,
     PromptCallback,
     ResponseCallback,
     RecalculateCallback,
     ctypes.POINTER(LLModelPromptContext),
+    ctypes.c_bool,
 ]
 
 llmodel.llmodel_prompt.restype = None
@@ -290,6 +292,7 @@ class LLModel:
     def prompt_model(
         self,
         prompt: str,
+        prompt_template: str,
         callback: ResponseCallbackType,
         n_predict: int = 4096,
         top_k: int = 40,
@@ -300,6 +303,7 @@ class LLModel:
         repeat_last_n: int = 10,
         context_erase: float = 0.75,
         reset_context: bool = False,
+        special: bool = False,
     ):
         """
         Generate response from model from a prompt.
@@ -326,9 +330,6 @@ class LLModel:
             prompt,
         )
 
-        prompt_bytes = prompt.encode()
-        prompt_ptr = ctypes.c_char_p(prompt_bytes)
-
         self._set_context(
             n_predict=n_predict,
             top_k=top_k,
@@ -343,16 +344,18 @@ class LLModel:
 
         llmodel.llmodel_prompt(
             self.model,
-            prompt_ptr,
+            ctypes.c_char_p(prompt.encode()),
+            ctypes.c_char_p(prompt_template.encode()),
             PromptCallback(self._prompt_callback),
             ResponseCallback(self._callback_decoder(callback)),
             RecalculateCallback(self._recalculate_callback),
             self.context,
+            special,
         )
 
 
     def prompt_model_streaming(
-        self, prompt: str, callback: ResponseCallbackType = empty_response_callback, **kwargs
+        self, prompt: str, prompt_template: str, callback: ResponseCallbackType = empty_response_callback, **kwargs
     ) -> Iterable[str]:
         output_queue: Queue[str | Sentinel] = Queue()
 
@@ -369,15 +372,15 @@ class LLModel:
 
             return _generator_callback
 
-        def run_llmodel_prompt(prompt: str, callback: ResponseCallbackType, **kwargs):
-            self.prompt_model(prompt, callback, **kwargs)
+        def run_llmodel_prompt(prompt: str, prompt_template: str, callback: ResponseCallbackType, **kwargs):
+            self.prompt_model(prompt, prompt_template, callback, **kwargs)
             output_queue.put(Sentinel.TERMINATING_SYMBOL)
 
         # Kick off llmodel_prompt in separate thread so we can return generator
         # immediately
         thread = threading.Thread(
             target=run_llmodel_prompt,
-            args=(prompt, _generator_callback_wrapper(callback)),
+            args=(prompt, prompt_template, _generator_callback_wrapper(callback)),
             kwargs=kwargs,
         )
         thread.start()

gpt4all-bindings/python/gpt4all/gpt4all.py

@@ -4,8 +4,10 @@ Python only API for running all GPT4All models.
 from __future__ import annotations
 
 import os
+import re
 import sys
 import time
+import warnings
 from contextlib import contextmanager
 from pathlib import Path
 from typing import Any, Dict, Iterable, List, Optional, Union
@@ -314,6 +316,10 @@ class GPT4All:
             Either the entire completion or a generator that yields the completion token by token.
         """
 
+        if re.search(r"%1(?![0-9])", self._current_prompt_template):
+            raise ValueError("Prompt template containing a literal '%1' is not supported. For a prompt "
+                             "placeholder, please use '{0}' instead.")
+
         # Preparing the model request
         generate_kwargs: Dict[str, Any] = dict(
             temp=temp,
@@ -327,16 +333,29 @@ class GPT4All:
 
         if self._is_chat_session_activated:
             # check if there is only one message, i.e. system prompt:
-            generate_kwargs["reset_context"] = len(self.current_chat_session) == 1
+            reset = len(self.current_chat_session) == 1
+            generate_kwargs["reset_context"] = reset
             self.current_chat_session.append({"role": "user", "content": prompt})
 
-            prompt = self._format_chat_prompt_template(
-                messages=self.current_chat_session[-1:],
-                default_prompt_header=self.current_chat_session[0]["content"]
-                if generate_kwargs["reset_context"]
-                else "",
-            )
+            if self._format_chat_prompt_template.__func__ is GPT4All._format_chat_prompt_template:
+                if reset:
+                    # ingest system prompt
+                    self.model.prompt_model(self.current_chat_session[0]["content"], "%1",
+                                            n_batch=n_batch, n_predict=0, special=True)
+                prompt_template = self._current_prompt_template.format("%1")
+            else:
+                warnings.warn(
+                    "_format_chat_prompt_template is deprecated. Please use a chat session with a prompt template.",
+                    DeprecationWarning,
+                )
+                # special tokens won't be processed
+                prompt = self._format_chat_prompt_template(
+                    self.current_chat_session[-1:],
+                    self.current_chat_session[0]["content"] if reset else "",
+                )
+                prompt_template = "%1"
         else:
+            prompt_template = "%1"
             generate_kwargs["reset_context"] = True
 
         # Prepare the callback, process the model response
@@ -365,14 +384,16 @@ class GPT4All:
         # Send the request to the model
         if streaming:
             return self.model.prompt_model_streaming(
-                prompt=prompt,
-                callback=_callback_wrapper(callback, output_collector),
+                prompt,
+                prompt_template,
+                _callback_wrapper(callback, output_collector),
                 **generate_kwargs,
             )
 
         self.model.prompt_model(
-            prompt=prompt,
-            callback=_callback_wrapper(callback, output_collector),
+            prompt,
+            prompt_template,
+            _callback_wrapper(callback, output_collector),
             **generate_kwargs,
         )
 
@@ -423,24 +444,6 @@ class GPT4All:
             Formatted prompt.
         """
 
-        if isinstance(default_prompt_header, bool):
-            import warnings
-
-            warnings.warn(
-                "Using True/False for the 'default_prompt_header' is deprecated. Use a string instead.",
-                DeprecationWarning,
-            )
-            default_prompt_header = ""
-
-        if isinstance(default_prompt_footer, bool):
-            import warnings
-
-            warnings.warn(
-                "Using True/False for the 'default_prompt_footer' is deprecated. Use a string instead.",
-                DeprecationWarning,
-            )
-            default_prompt_footer = ""
-
         full_prompt = default_prompt_header + "\n\n" if default_prompt_header != "" else ""
 
         for message in messages: